Underwater flexible compressed air energy storage configuration method for offshore wind power absorption

Abstract

The invention discloses an underwater flexible compressed air energy storage configuration method for offshore wind power absorption, which belongs to the technical field of novel energy and comprises the following steps: S1, constructing an offshore wind storage power station configuration model; s2, constructing an offshore wind power output box type uncertainty set; and S3, according to the offshore wind power output box type uncertainty set, solving the offshore wind storage power station configuration model, and completing underwater flexible compressed air energy storage configuration. According to the capacity configuration method for the underwater flexible compressed air energy storage system, the underwater compressed air energy storage technology and the flexible air bag air storage device are innovatively combined, the energy storage bottleneck in offshore wind power consumption is effectively solved, the limitation of traditional land-based energy storage is broken through, the energy storage capacity is optimized, and the energy storage efficiency is improved. And the economical efficiency of offshore wind power matched energy storage construction is obviously improved.

Description

Technical Field

[0001] This invention belongs to the field of new energy technology, specifically relating to a method for configuring underwater flexible compressed air energy storage for offshore wind power consumption. Background Technology

[0002] With the increasing global demand for clean energy and growing environmental awareness, offshore wind power, as an important renewable energy source, is developing at an increasingly rapid pace. However, offshore wind power suffers from intermittency and instability, posing a challenge to the stable operation of the power grid. How to effectively absorb offshore wind power has become a crucial issue facing the energy sector. Among various energy storage technologies, compressed air energy storage (CAES), as a large-scale and long-cycle energy storage method, has promising application prospects. Traditional CAES systems are mostly built on land, but due to geographical location and geological conditions, they are difficult to directly apply to the energy storage needs of offshore wind farms. Underwater CAES systems based on flexible airbags offer the advantage of constant pressure operation; however, the deployment of underwater CAES systems presents certain construction challenges. Therefore, it is necessary to study a capacity configuration method for CAES systems geared towards offshore wind power absorption to improve the economic efficiency of the system's initial construction. Summary of the Invention

[0003] To address the above problems, this invention proposes a method for configuring underwater flexible compressed air energy storage for offshore wind power consumption.

[0004] The technical solution of this invention is: a method for configuring underwater flexible compressed air energy storage for offshore wind power consumption, comprising the following steps: S1. Construct a configuration model for offshore wind-storage power stations; S2. Constructing the box-type uncertainty set of offshore wind power output; S3. Based on the uncertain set of offshore wind power output boxes, solve the configuration model of offshore wind power storage stations to complete the underwater flexible compressed air energy storage configuration.

[0005] Furthermore, S1 includes the following sub-steps: S11. Calculate the total investment cost of the energy storage power station; S12. Calculate the operation and maintenance costs of the wind-storage power station; S13. Calculate the cost of wind curtailment of the power output of an offshore wind storage power station; S14. Based on the total investment cost of the energy storage power station, the operation and maintenance cost of the wind storage power station, and the wind curtailment cost of the offshore wind storage power station, construct a configuration model for the offshore wind storage power station.

[0006] Furthermore, in S11, the total investment cost of the energy storage power station C inv The expression is: ; In the formula, This indicates the rated compression power of the underwater compressed air energy storage system. This indicates the expansion power of the underwater compressed air energy storage system. V a This indicates the maximum volume of the flexible airbag. This represents the unit construction cost of the compression subsystem. This represents the unit construction cost of the expansion subsystem. This indicates the unit construction cost of the gas storage system. Indicates the isochronous value coefficient; In S12, the operation and maintenance costs of wind-storage power plants C opm The expression: ; In the formula, express t The compression power of the energy storage system during the time period, This represents the expansion power of the energy storage system during time period t. This represents the unit maintenance cost of the compression subsystem. This represents the unit operation and maintenance cost of the expansion subsystem. This indicates the unit operation and maintenance cost of the gas storage system; In S13, the cost of wind curtailment of offshore wind storage power station output. C pw The expression is: ; In the formula, express t The amount of wind curtailment at the wind-storage power station during the specified period. C pendlty This indicates the penalty unit price.

[0007] Furthermore, in S14, the expression for the configuration model of an offshore wind-storage power station is: ; In the formula, U This represents all scenarios involving wind power output. C inv This represents the total investment cost of an energy storage power station. C opm This indicates the operation and maintenance costs of a wind-storage power station. C pw This indicates the cost of wind curtailment for the output of an offshore wind-storage power station; The expressions for the upper and lower limits of the configuration capacity constraints in the offshore wind-storage power station configuration model are as follows: ; In the formula, This indicates the minimum value of the rated compression power of the parameter to be configured. This indicates the maximum value of the rated compression power of the parameter to be configured. This represents the minimum value of the rated expansion power. This indicates the maximum value of the rated expansion power. This indicates the minimum volume of the gas-storage bladder. This indicates the maximum volume of the gas-storage airbag. V a This indicates the maximum volume of the flexible airbag. This indicates the rated compression power of the underwater compressed air energy storage system. This indicates the expansion power of the underwater compressed air energy storage system; The expression for the operating constraints of the underwater compressed air energy storage system in the configuration model of an offshore wind power station is as follows: ; In the formula, This indicates the lower limit of the real-time charging power for underwater compressed air energy storage. This indicates the upper limit of real-time charging power for underwater compressed air energy storage. This indicates the lower limit of the real-time discharge power of underwater compressed air energy storage. This indicates the upper limit of real-time discharge power for underwater compressed air energy storage. express t The compression power of the energy storage system during the time period, This represents the expansion power of the energy storage system during time period t. express t The 0-1 variable representing the time period in which the underwater compressed air energy storage system is in a compressed state. express t The 0-1 variable representing the time period in which the underwater compressed air energy storage system is in an expanded state. This indicates the mass flow rate of air entering the compressor. This indicates the mass flow rate of air entering the expander. η C This represents the compression mechanical loss coefficient of the system. η G This represents the expansion mechanical loss coefficient of the system. This indicates the temperature of the air entering the compressor. This indicates the temperature of the air entering the expander. π C Indicates the isentropic efficiency of compression. π G This indicates the isentropic efficiency of the expansion. λ Indicates the air insulation coefficient. c p This indicates the specific heat capacity of air at constant pressure. βC Indicates the compression ratio. β G Indicates the expansion ratio. к Indicates the air insulation coefficient. R Represents the ideal gas constant. T A This indicates the air temperature inside the flexible airbag. p a This indicates the air pressure inside the flexible airbag; The expression for the transmission line capacity constraint in the configuration model of an offshore wind-storage power station is as follows: ; In the formula, Indicates the output of offshore wind power. This indicates the upper limit of the transmission line capacity.

[0008] Furthermore, in S2, the expression for the box-type uncertainty set of offshore wind power output is: ; In the formula, Г1 represents the lower bound coefficient of the box-type uncertainty set, and Г2 represents the upper bound coefficient of the box-type uncertainty set. P w This indicates the power output of offshore wind power.

[0009] Furthermore, S3 includes the following sub-steps: S31. Transform the configuration model of the offshore wind-storage power station to obtain the problem to be solved; S32. Break down the problem to be solved into a main problem and sub-problems; S33. Determine the fluctuation range of offshore wind power output based on the box-type uncertainty set of offshore wind power output; S34. Based on the fluctuation range of offshore wind power output, the main problem and sub-problems are solved using the column and constraint generation algorithm to determine the rated parameters and transmission line capacity of underwater flexible compressed air energy storage.

[0010] Furthermore, in S31, the expression for the problem to be solved is: ; In the formula, A This represents the coefficient vector in the objective function that is related to the variables of the first-stage optimization problem. B This represents the coefficient vector in the objective function that is related to the variables in the second-stage optimization problem. C This represents the coefficient matrix of continuous variables in the first-stage optimization problem within the upper and lower capacity constraints. d This represents the constant vector in the upper and lower limits of the configuration capacity constraints. E The coefficient matrix represents the continuous variables in the first-stage optimization problem under the running constraints and transmission capacity constraints. FThe coefficient matrix represents the 0-1 variables of the second-stage optimization problem in the context of runtime constraints and transmission capacity constraints. G The coefficient matrix represents the continuous variables in the second-stage optimization problem under the running constraints and transmission capacity constraints. H This represents the coefficient matrix of uncertain variables in the operational constraints and transmission capacity constraints. k This represents the constant vector in the operational constraints and transmission capacity constraints. x This represents a continuous variable in the first stage of the optimization problem. y Describing the 0-1 variables in the second-stage optimization problem. z Represents continuous variables in the second-stage optimization problem. u It represents an uncertain variable.

[0011] Furthermore, in S32, the expression for the main problem is: ; In the formula, A This represents the coefficient vector in the objective function that is related to the variables of the first-stage optimization problem. B This represents the coefficient vector in the objective function that is related to the variables in the second-stage optimization problem. C This represents the coefficient matrix of continuous variables in the first-stage optimization problem within the upper and lower capacity constraints. d This represents the constant vector in the upper and lower limits of the configuration capacity constraints. E The coefficient matrix represents the continuous variables in the first-stage optimization problem under the running constraints and transmission capacity constraints. F The coefficient matrix represents the 0-1 variables of the second-stage optimization problem in the context of runtime constraints and transmission capacity constraints. G The coefficient matrix represents the continuous variables in the second-stage optimization problem under the running constraints and transmission capacity constraints. H This represents the coefficient matrix of uncertain variables in the operational constraints and transmission capacity constraints. x This represents a continuous variable in the first stage of the optimization problem. y Describing the 0-1 variables in the second-stage optimization problem. z Represents continuous variables in the second-stage optimization problem. u Represents an uncertain variable. γ This indicates the introduced intermediate variable. r This indicates the number of iterations in the first phase of the problem; The expression for the subproblem is: ; In the formula, This represents the value of the first variable obtained from solving the main problem. This represents the value of the second variable obtained from solving the main problem. π This represents the dual variable established based on the KKT conditions. kThis represents the constant vector in the operational constraints and transmission capacity constraints.

[0012] The beneficial effects of this invention are as follows: The underwater flexible compressed air energy storage system capacity configuration method proposed in this invention, by innovatively combining underwater compressed air energy storage technology with flexible airbag storage device, effectively solves the energy storage bottleneck in offshore wind power consumption, breaks through the limitations of traditional land-based energy storage, and significantly improves the economic efficiency of offshore wind power supporting energy storage construction by optimizing energy storage capacity. Attached Figure Description

[0013] Figure 1 A flowchart illustrating a method for configuring underwater flexible compressed air energy storage for offshore wind power integration; Figure 2 This is a structural diagram of an offshore wind power storage system. Detailed Implementation

[0014] The embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0015] like Figure 1 As shown, this invention provides a method for configuring underwater flexible compressed air energy storage for offshore wind power consumption, including the following steps: S1. Construct a configuration model for offshore wind-storage power stations; S2. Constructing the box-type uncertainty set of offshore wind power output; S3. Based on the uncertain set of offshore wind power output boxes, solve the configuration model of offshore wind power storage stations to complete the underwater flexible compressed air energy storage configuration.

[0016] This invention first establishes a configuration model for an offshore wind-storage power station, including an offshore wind farm, a subsea flexible compressed air energy storage system, and transmission lines. Furthermore, since accurate wind power forecasts are unavailable, a Monte Carlo method is used to establish a box-shaped uncertainty set for offshore wind power output. Finally, a column and constraint generation method is employed to solve the capacity configuration problem of the combined offshore wind-storage power station, obtaining the rated parameters of the subsea flexible compressed air energy storage and the transmission line capacity.

[0017] In this embodiment of the invention, S1 includes the following sub-steps: S11. Calculate the total investment cost of the energy storage power station; S12. Calculate the operation and maintenance costs of the wind-storage power station; S13. Calculate the cost of wind curtailment of the power output of an offshore wind storage power station; S14. Based on the total investment cost of the energy storage power station, the operation and maintenance cost of the wind storage power station, and the wind curtailment cost of the offshore wind storage power station, construct a configuration model for the offshore wind storage power station.

[0018] like Figure 2The diagram shows a configuration model for an offshore wind power storage station, mainly comprising an offshore wind farm, an underwater flexible compressed air energy storage system, and transmission lines. This invention establishes a configuration model for an offshore wind power storage station, including an offshore wind farm, an underwater flexible compressed air energy storage system, and transmission lines. The electricity output from the wind power storage station is transmitted to the power grid via transmission lines. Due to the fluctuating power output of the offshore wind farm, surplus electricity exceeding the transmission line capacity is used to drive the compressor of the underwater flexible compressed air energy storage system, compressing air to a high-pressure state and storing it in an underwater flexible airbag. When the offshore wind turbine's power generation is insufficient and the transmission line capacity has not reached its limit, the underwater flexible compressed air energy storage system is in an expansion and power generation state, with high-pressure air released from the underwater flexible airbag to drive the expander and generate electricity. When both the underwater airbag's storage capacity and the transmission line capacity reach their limits, surplus wind power is discarded. The upper limit of the output of offshore wind turbines is determined by the wind energy resources at the site; the charging and discharging power and state of charge of energy storage cannot exceed their own upper and lower limits; the total power transmitted from the wind-storage power station to the grid is not allowed to exceed the capacity of the transmission line. Considering the above constraints, an offshore wind-storage power station configuration model is established with the objective function of minimizing the construction cost of the underwater compressed air energy storage system and the transmission line.

[0019] In this embodiment of the invention, in S11, the total investment cost of the energy storage power station includes the investment cost of the compression system, the investment cost of the expansion system, and the investment cost of the gas storage system; the total investment cost of the energy storage power station C inv The expression is: ; In the formula, This indicates the rated compression power of the underwater compressed air energy storage system. This indicates the expansion power of the underwater compressed air energy storage system. V a This indicates the maximum volume of the flexible airbag. This represents the unit construction cost of the compression subsystem. This represents the unit construction cost of the expansion subsystem. This indicates the unit construction cost of the gas storage system. Indicates the isochronous value coefficient; The annual value factor can be used with the investment discount rate. r y and the lifespan of compressed air energy storage T The calculation is expressed as follows: .

[0020] In S12, the operation and maintenance costs of wind-storage power plants C opm The expression: ; In the formula, express t The compression power of the energy storage system during the time period, This represents the expansion power of the energy storage system during time period t. This represents the unit maintenance cost of the compression subsystem. This represents the unit operation and maintenance cost of the expansion subsystem. This indicates the unit operation and maintenance cost of the gas storage system; In S13, the cost of wind curtailment of offshore wind storage power station output. C pw The expression is: ; In the formula, express t The amount of wind curtailment at the wind-storage power station during the specified period. C pendlty This indicates the penalty unit price.

[0021] In this embodiment of the invention, in S14, the expression for the offshore wind-storage power station configuration model is: ; In the formula, U This represents all scenarios involving wind power output. C inv This represents the total investment cost of an energy storage power station. C opm This indicates the operation and maintenance costs of a wind-storage power station. C pw This indicates the cost of wind curtailment for the output of an offshore wind-storage power station; The expressions for the upper and lower limits of the configuration capacity constraints in the offshore wind-storage power station configuration model are as follows: ; In the formula, This indicates the minimum value of the rated compression power of the parameter to be configured. This indicates the maximum value of the rated compression power of the parameter to be configured. This represents the minimum value of the rated expansion power. This indicates the maximum value of the rated expansion power. This indicates the minimum volume of the gas-storage bladder. This indicates the maximum volume of the gas-storage airbag. V a This indicates the maximum volume of the flexible airbag. This indicates the rated compression power of the underwater compressed air energy storage system. This indicates the expansion power of the underwater compressed air energy storage system; The expression for the operating constraints of the underwater compressed air energy storage system in the configuration model of an offshore wind power station is as follows: ; In the formula, This indicates the lower limit of the real-time charging power for underwater compressed air energy storage. This indicates the upper limit of real-time charging power for underwater compressed air energy storage. This indicates the lower limit of the real-time discharge power of underwater compressed air energy storage. This indicates the upper limit of real-time discharge power for underwater compressed air energy storage. express t The compression power of the energy storage system during the time period, This represents the expansion power of the energy storage system during time period t. express t The 0-1 variable representing the time period in which the underwater compressed air energy storage system is in a compressed state. express t The 0-1 variable representing the time period in which the underwater compressed air energy storage system is in an expanded state. This indicates the mass flow rate of air entering the compressor. This indicates the mass flow rate of air entering the expander. η C This represents the compression mechanical loss coefficient of the system. η G This represents the expansion mechanical loss coefficient of the system. This indicates the temperature of the air entering the compressor. This indicates the temperature of the air entering the expander. π C Indicates the isentropic efficiency of compression. π G This indicates the isentropic efficiency of the expansion. λ Indicates the air insulation coefficient. c p This indicates the specific heat capacity of air at constant pressure. β C Indicates the compression ratio. β G Indicates the expansion ratio. к Indicates the air insulation coefficient. R Represents the ideal gas constant. T A This indicates the air temperature inside the flexible airbag. p a This indicates the air pressure inside the flexible airbag; Constraints 1 and 2 represent the charging and discharging power constraints of the energy storage system. Constraint 3 indicates that the system cannot be in both compression and expansion conditions simultaneously. Constraints 4 and 5 represent the relationship between the charging and discharging power of the energy storage system and the air mass flow rate.

[0022] The expression for the transmission line capacity constraint in the configuration model of an offshore wind-storage power station is as follows: ; In the formula, Indicates the output of offshore wind power. This indicates the upper limit of the transmission line capacity.

[0023] In this embodiment of the invention, in step S2, firstly, 8760 samples of past annual wind speed values ​​at the offshore wind farm site are selected, and typical wind power output scenarios for each time period within a 24-hour operating cycle are obtained using the Monte Carlo method. Then, error coefficients are selected to establish a box-shaped uncertainty set for offshore wind power output. The expression for the box-shaped uncertainty set of offshore wind power output is: ; In the formula, Г1 represents the lower bound coefficient of the box-type uncertainty set, and Г2 represents the upper bound coefficient of the box-type uncertainty set. P w This indicates the power output of offshore wind power.

[0024] In this embodiment of the invention, S3 includes the following sub-steps: S31. Transform the configuration model of the offshore wind-storage power station to obtain the problem to be solved; S32. Break down the problem to be solved into a main problem and sub-problems; S33. Determine the fluctuation range of offshore wind power output based on the box-type uncertainty set of offshore wind power output; S34. Based on the fluctuation range of offshore wind power output, the main problem and sub-problems are solved using the column and constraint generation algorithm to determine the rated parameters and transmission line capacity of underwater flexible compressed air energy storage.

[0025] In this embodiment of the invention, in S31, the expression of the problem to be solved is: ; In the formula, A This represents the coefficient vector in the objective function that is related to the variables of the first-stage optimization problem. B This represents the coefficient vector in the objective function that is related to the variables in the second-stage optimization problem. C This represents the coefficient matrix of continuous variables in the first-stage optimization problem within the upper and lower capacity constraints. d This represents the constant vector in the upper and lower limits of the configuration capacity constraints. E The coefficient matrix represents the continuous variables in the first-stage optimization problem under the running constraints and transmission capacity constraints. F The coefficient matrix represents the 0-1 variables of the second-stage optimization problem in the context of runtime constraints and transmission capacity constraints. G The coefficient matrix represents the continuous variables in the second-stage optimization problem under the running constraints and transmission capacity constraints. H This represents the coefficient matrix of uncertain variables in the operational constraints and transmission capacity constraints.k This represents the constant vector in the operational constraints and transmission capacity constraints. x This represents a continuous variable in the first stage of the optimization problem. y Describing the 0-1 variables in the second-stage optimization problem. z Represents continuous variables in the second-stage optimization problem. u It represents an uncertain variable.

[0026] The continuous variables in the first-stage optimization problem include the parameters to be configured: rated compression power, rated expansion power, air storage bladder volume, and transmission line capacity. The 0-1 variables in the first-stage optimization problem include the charging and discharging state of the underwater compressed air energy storage system. The continuous variables in the second-stage optimization problem include the air storage tank filling volume, compression power, expansion power, and transmission line power of the underwater compressed air energy storage system. The uncertain variable is the offshore wind power.

[0027] In this embodiment of the invention, in S32, the expression of the main problem is: ; In the formula, A This represents the coefficient vector in the objective function that is related to the variables of the first-stage optimization problem. B This represents the coefficient vector in the objective function that is related to the variables in the second-stage optimization problem. C This represents the coefficient matrix of continuous variables in the first-stage optimization problem within the upper and lower capacity constraints. d This represents the constant vector in the upper and lower limits of the configuration capacity constraints. E The coefficient matrix represents the continuous variables in the first-stage optimization problem under the running constraints and transmission capacity constraints. F The coefficient matrix represents the 0-1 variables of the second-stage optimization problem in the context of runtime constraints and transmission capacity constraints. G The coefficient matrix represents the continuous variables in the second-stage optimization problem under the running constraints and transmission capacity constraints. H This represents the coefficient matrix of uncertain variables in the operational constraints and transmission capacity constraints. x This represents a continuous variable in the first stage of the optimization problem. y Describing the 0-1 variables in the second-stage optimization problem. z Represents continuous variables in the second-stage optimization problem. u Represents an uncertain variable. γ This indicates the introduced intermediate variable. r Indicates the number of iterations in the first phase of the problem; with r The superscript parameter is the first r The decision variables established during the iteration to solve the main problem. The objective function value of the main problem corresponds to the lower bound of the original configuration problem.

[0028] The expression for the subproblem is: ; In the formula, This represents the value of the first variable obtained from solving the main problem. This represents the value of the second variable obtained from solving the main problem. π This represents the dual variable established based on the KKT conditions. k This represents the constant vector in the operational constraints and transmission capacity constraints.

[0029] The second constraint of the subproblem can be linearized using the Big M condition, thus transforming it into a mixed-integer linear programming problem solvable by commercial solvers. The objective function value of the subproblem corresponds to the upper bound of the original collocation problem. When When the problem is considered to have converged, the loop terminates and the final configuration value is obtained, where, UB This represents the upper bound of the original configuration problem. LB This represents the lower bound of the original configuration problem.

[0030] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A method for configuring underwater flexible compressed air energy storage for offshore wind power consumption, characterized in that, Includes the following steps: S1. Construct a configuration model for offshore wind-storage power stations; S2. Constructing the box-type uncertainty set of offshore wind power output; S3. Based on the uncertain set of offshore wind power output boxes, solve the configuration model of offshore wind power storage stations to complete the underwater flexible compressed air energy storage configuration.

2. The underwater flexible compressed air energy storage configuration method for offshore wind power consumption according to claim 1, characterized in that, S1 includes the following sub-steps: S11. Calculate the total investment cost of the energy storage power station; S12. Calculate the operation and maintenance costs of the wind-storage power station; S13. Calculate the cost of wind curtailment of the power output of an offshore wind storage power station; S14. Based on the total investment cost of the energy storage power station, the operation and maintenance cost of the wind storage power station, and the wind curtailment cost of the offshore wind storage power station, construct a configuration model for the offshore wind storage power station.

3. The underwater flexible compressed air energy storage configuration method for offshore wind power consumption according to claim 2, characterized in that, In S11, the total investment cost of the energy storage power station C inv The expression is: ； In the formula, This indicates the rated compression power of the underwater compressed air energy storage system. This indicates the expansion power of the underwater compressed air energy storage system. V a This indicates the maximum volume of the flexible airbag. This represents the unit construction cost of the compression subsystem. This represents the unit construction cost of the expansion subsystem. This indicates the unit construction cost of the gas storage system. Indicates the isochronous value coefficient; In S12, the operation and maintenance cost of the wind-storage power station C opm The expression: ； In the formula, express t The compression power of the energy storage system during the time period, This represents the expansion power of the energy storage system during time period t. This represents the unit maintenance cost of the compression subsystem. This represents the unit operation and maintenance cost of the expansion subsystem. This indicates the unit operation and maintenance cost of the gas storage system; In S13, the cost of wind curtailment of the offshore wind storage power station's output. C pw The expression is: ； In the formula, express t The amount of wind curtailment at the wind-storage power station during the specified period. C pendlty This indicates the penalty unit price.

4. The underwater flexible compressed air energy storage configuration method for offshore wind power consumption according to claim 2, characterized in that, In S14, the expression for the offshore wind-storage power station configuration model is: ； In the formula, U This represents all scenarios involving wind power output. C inv This represents the total investment cost of an energy storage power station. C opm This indicates the operation and maintenance costs of a wind-storage power station. C pw This indicates the cost of wind curtailment for the output of an offshore wind-storage power station; The expressions for the upper and lower limit constraints of the configuration capacity of the offshore wind-storage power station configuration model are as follows: ； In the formula, This indicates the minimum value of the rated compression power of the parameter to be configured. This indicates the maximum value of the rated compression power of the parameter to be configured. This represents the minimum value of the rated expansion power. This indicates the maximum value of the rated expansion power. This indicates the minimum volume of the gas-storage bladder. This indicates the maximum volume of the gas-storage bladder. V a This indicates the maximum volume of the flexible airbag. This indicates the rated compression power of the underwater compressed air energy storage system. This indicates the expansion power of the underwater compressed air energy storage system; The expression for the operating constraints of the underwater compressed air energy storage system in the offshore wind power station configuration model is as follows: ； In the formula, This indicates the lower limit of the real-time charging power for underwater compressed air energy storage. This indicates the upper limit of real-time charging power for underwater compressed air energy storage. This indicates the lower limit of the real-time discharge power of underwater compressed air energy storage. This indicates the upper limit of real-time discharge power for underwater compressed air energy storage. express t The compression power of the energy storage system during the time period, This represents the expansion power of the energy storage system during time period t. express t The 0-1 variable representing the time period in which the underwater compressed air energy storage system is in a compressed state. express t The 0-1 variable representing the time period in which the underwater compressed air energy storage system is in an expanded state. This indicates the mass flow rate of air entering the compressor. This indicates the mass flow rate of air entering the expander. η C This represents the compression mechanical loss coefficient of the system. η G This represents the expansion mechanical loss coefficient of the system. This indicates the temperature of the air entering the compressor. This indicates the temperature of the air entering the expander. π C Indicates the isentropic efficiency of compression. π G This indicates the isentropic efficiency of the expansion. λ Indicates the air insulation coefficient. c p This indicates the specific heat capacity of air at constant pressure. β C Indicates the compression ratio. β G Indicates the expansion ratio. к Indicates the air insulation coefficient. R Represents the ideal gas constant. T A This indicates the air temperature inside the flexible airbag. p a This indicates the air pressure inside the flexible airbag; The expression for the transmission line capacity constraint of the offshore wind power storage station configuration model is as follows: ； In the formula, Indicates the output of offshore wind power. This indicates the upper limit of the transmission line capacity.

5. The underwater flexible compressed air energy storage configuration method for offshore wind power consumption according to claim 1, characterized in that, In S2, the expression for the box-type uncertainty set of offshore wind power output is: ； In the formula, Г1 represents the lower bound coefficient of the box-type uncertainty set, and Г2 represents the upper bound coefficient of the box-type uncertainty set. P w This indicates the power output of offshore wind power.

6. The underwater flexible compressed air energy storage configuration method for offshore wind power consumption according to claim 1, characterized in that, S3 includes the following sub-steps: S31. Transform the configuration model of the offshore wind-storage power station to obtain the problem to be solved; S32. Break down the problem to be solved into a main problem and sub-problems; S33. Determine the fluctuation range of offshore wind power output based on the box-type uncertainty set of offshore wind power output; S34. Based on the fluctuation range of offshore wind power output, the main problem and sub-problems are solved using the column and constraint generation algorithm to determine the rated parameters and transmission line capacity of underwater flexible compressed air energy storage.

7. The underwater flexible compressed air energy storage configuration method for offshore wind power consumption according to claim 6, characterized in that, In S31, the expression for the problem to be solved is: ； In the formula, A This represents the coefficient vector in the objective function that is related to the variables of the first-stage optimization problem. B This represents the coefficient vector in the objective function that is related to the variables in the second-stage optimization problem. C This represents the coefficient matrix of continuous variables in the first-stage optimization problem within the upper and lower capacity constraints. d This represents the constant vector in the upper and lower limits of the configuration capacity constraints. E The coefficient matrix represents the continuous variables in the first-stage optimization problem under the running constraints and transmission capacity constraints. F The coefficient matrix represents the 0-1 variables of the second-stage optimization problem in the context of runtime constraints and transmission capacity constraints. G The coefficient matrix represents the continuous variables in the second-stage optimization problem under the running constraints and transmission capacity constraints. H This represents the coefficient matrix of uncertain variables in the operational constraints and transmission capacity constraints. k This represents the constant vector in the operational constraints and transmission capacity constraints. x This represents a continuous variable in the first stage of the optimization problem. y Describing the 0-1 variables in the second-stage optimization problem. z Represents continuous variables in the second-stage optimization problem. u It represents an uncertain variable.

8. The underwater flexible compressed air energy storage configuration method for offshore wind power consumption according to claim 6, characterized in that, In S32, the expression for the main problem is: ； In the formula, A This represents the coefficient vector in the objective function that is related to the variables of the first-stage optimization problem. B This represents the coefficient vector in the objective function that is related to the variables in the second-stage optimization problem. C This represents the coefficient matrix of continuous variables in the first-stage optimization problem within the upper and lower capacity constraints. d This represents the constant vector in the upper and lower limits of the configuration capacity constraints. E The coefficient matrix represents the continuous variables in the first-stage optimization problem under the running constraints and transmission capacity constraints. F The coefficient matrix represents the 0-1 variables of the second-stage optimization problem in the context of runtime constraints and transmission capacity constraints. G The coefficient matrix represents the continuous variables in the second-stage optimization problem under the running constraints and transmission capacity constraints. H This represents the coefficient matrix of uncertain variables in the operational constraints and transmission capacity constraints. x This represents a continuous variable in the first stage of the optimization problem. y Describing the 0-1 variables in the second-stage optimization problem. z Represents continuous variables in the second-stage optimization problem. u Represents an uncertain variable. γ This indicates the introduced intermediate variable. r This indicates the number of iterations in the first phase of the problem; The expression for the subproblem is: ； In the formula, This represents the value of the first variable obtained from solving the main problem. This represents the value of the second variable obtained from solving the main problem. π This represents the dual variable established based on the KKT conditions. k This represents the constant vector in the operational constraints and transmission capacity constraints.

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